{"id":"W2896642556","doi":"10.1109/tap.2018.2876649","title":"Integrating Physics-Based Wireless Propagation Models and Network Protocol Design for Train Communication Systems","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Antennas and Propagation","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Path loss; Computer science; Robustness (evolution); Network planning and design; Communications protocol; Fidelity; Wireless network; Radio propagation; Wireless; Radio propagation model; Protocol (science); Distributed computing; Simulation; Computer network; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005597716,0.0002311003,0.0002131221,0.00009947485,0.000496654,0.000163771,0.00007514447,0.0001189926,0.000004960837],"category_scores_gemma":[0.000004997063,0.0002124983,0.00004620292,0.000195338,0.00009700118,0.0003777055,0.000001139398,0.0001844677,0.000002227408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005853678,"about_ca_system_score_gemma":0.00003507213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001656151,"about_ca_topic_score_gemma":0.00002320299,"domain_scores_codex":[0.9988238,0.0001343723,0.0003910371,0.0002679648,0.0001478332,0.0002349672],"domain_scores_gemma":[0.9992405,0.0001155121,0.0001042248,0.0002072263,0.0002554235,0.000077082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002667536,0.00007049354,0.000001976021,0.0004399849,0.0000485158,1.81311e-7,0.0009138078,0.8264346,0.05109868,0.001149218,0.00005128476,0.1195245],"study_design_scores_gemma":[0.0008523032,0.0003151071,0.000002720831,0.0003487309,0.00003298346,0.00000373111,0.0001148001,0.9408034,0.05585222,0.001382819,0.00005761545,0.0002335492],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002943637,0.0000358712,0.9752148,0.00006204172,0.0001538706,0.02120681,0.00001544265,0.0002585037,0.0001090767],"genre_scores_gemma":[0.9489278,0.00002849448,0.02717022,0.00005785323,0.0001245946,0.02358956,0.00001791197,0.0000520096,0.00003155855],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9480445,"threshold_uncertainty_score":0.8665428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05366745347007556,"score_gpt":0.2710930349913243,"score_spread":0.2174255815212487,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}